# coding: utf-8
"""A very simple MNIST classifier.
See extensive documentation at
https://www.tensorflow.org/get_started/mnist/beginners
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import sys

from tensorflow.examples.tutorials.mnist import input_data

from keras.layers.core import Dense,Flatten
from keras.layers.convolutional import Conv2D
from keras.layers.pooling import MaxPooling2D

from keras import backend as K

print(K.image_data_format())

import tensorflow as tf

FLAGS = None
# Import data
data_dir = '/tmp/tensorflow/mnist/input_data'
mnist = input_data.read_data_sets(data_dir, one_hot=True)


# Create the model
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.matmul(x, W) + b

# Define loss and optimizer
y_ = tf.placeholder(tf.float32, [None, 10])